Objective: High-density lipoprotein (HDL) consists of diverse subfractions, each with unique roles in cardiovascular health and disease. This study aimed to evaluate the clinical utility of HDL2b quantification via microfluidic chip electrophoresis (MCE) for acute coronary syndrome (ACS) as prediction and compare its diagnostic performance with conventional lipid parameters. Methods: This retrospective study analyzed 230 participants (126 ACS patients vs. 104 age/sex-matched controls) from Gaozhou People's Hospital (2020-2021). HDL subfractions were quantified using the MICEP-30 MCE system. Univariable logistic regression and receiver operating characteristic (ROC) analyses were performed to assess associations and diagnostic accuracy. Results: The analysis revealed significantly lower HDL2b concentrations in ACS patients compared to controls (median: 248.30 vs. 399.68 μmol/L, p<0.001), with no significant difference in HDL3 (p=0.839). Logistic regression identified HDL2b as the strongest independent predictor of ACS (OR: 0.988 per μmol/L increase, 95% CI: 0.985-0.992, p<0.001), outperforming traditional HDL-C (OR: 0.007) and triglycerides (OR: 1.999). ROC analysis demonstrated HDL2b's superior diagnostic accuracy (AUC: 0.822, 81.0% sensitivity/70.2% specificity at 333.165 μmol/L cutoff), surpassing HDL-C (AUC: 0.810) and other lipid parameters (TG AUC: 0.606, LDL-C AUC: 0.606), while HDL3 showed no discriminative capacity (AUC: 0.508). These findings position HDL2b quantified by microfluidic electrophoresis as a clinically superior biomarker for ACS prediction. Conclusions: HDL2b quantification via MCE emerges as a rapid, precise diagnostic tool for ACS prediction, demonstrating significant advantages over traditional lipid parameters. This technology enables clinically actionable HDL subfraction profiling, with the potential to significantly improve cardiovascular risk stratification paradigms.

Background and purposeDiabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). High-density lipoprotein cholesterol (HDL-C) has traditionally been considered renoprotective, yet growing evidence suggests that HDL subclasses may differ in biological function. This study aimed to investigate the association between HDL subclasses, particularly HDL2b, and chronic kidney disease (CKD) in Chinese adults with T2DM.MethodsIn this cross-sectional study, patients with T2DM were enrolled. CKD was defined as urinary albumin-to-creatinine ratio (UACR) ≥3.0 mg/mmol and/or estimated glomerular filtration rate (eGFR) ≤60 mL/min/1.73 m². HDL subclasses were measured using capillary electrophoresis-based microfluidics. Participants were categorized into quartiles of HDL-C, HDL2b, and HDL3. Multivariable logistic regression models were constructed with progressive adjustment for anthropometric indices, hypertension, insulin resistance (HOMA-IR), and inflammatory markers.ResultsAmong 481 patients with T2DM, 136 (28.3%) had CKD. Patients with CKD exhibited significantly lower HDL2b levels (P = 0.001), together with greater insulin resistance and systemic inflammation (all P<0.05). HDL2b showed stronger inverse correlations than total HDL-C with adiposity, glycemic indices, insulin resistance, and inflammatory markers (all P<0.05). In multivariable logistic regression, higher HDL2b was independently associated with a lower risk of CKD. Compared with the lowest quartile, the third and fourth quartiles were associated with reduced odds of CKD (Q3: OR = 0.425, 95% CI 0.220–0.821, P = 0.012; Q4: OR = 0.367, 95% CI 0.188–0.717, P = 0.001). The inverse association between HDL2b and CKD was stronger in participants with higher insulin resistance (P for interaction=0.044).ConclusionHigher HDL2b, but not total HDL-C or HDL3, is independently associated with lower risk of CKD in T2DM. HDL2b may serve as a sensitive biomarker for early renal risk stratification.

Aim: High-density lipoprotein (HDL) can be divided into several subfractions based on density, size and composition. Accumulative evidence strongly suggests that the subfractions of HDL have very different roles in the pathogenesis of atherosclerosis. The purpose of this study was to further delineate the relationship between HDL subfractions extracted by microfluidic chip electrophoresis and the vulnerability of plaques in patients with intracranial atherosclerosis with a high-resolution magnetic resonance imaging (HRMRI) study. Methods: We prospectively enrolled patients with single atherosclerotic plaque in the middle cerebral artery (MCA) or basilar artery (BA) between July 2020 and Dec 2022 and performed 3-tesla HRMRI on the relevant artery. The HDL cholesterol concentration and HDL subfractions (HDL-2a, HDL-2b and HDL-3) percentage were analyzed in serum samples from the same patients by electrophoresis on a microfluidics system.Results: A total of 81 MCA or BA plaques [38 (46.9%) symptomatic and 43 (53.1%) asymptomatic] in 81 patients were identified on HRMRI. Patients with symptomatic plaques had a significantly lower HDL-2b level than asymptomatic plaques [symptomatic vs. asymptomatic: 0.16 (0.10-0.18) vs. 0.27(0.21-0.34), p = 0.001]. After adjusting for demographics and vascular risk factors, logistic regression showed that HDL-2b was inversely associated with asymptomatic plaques (B = -0.04, P = 0.017). According to receiver operating characteristic (ROC) curve model analysis, the cutoff point of HDL-2b in predicting asymptomatic plaques was 0.21 mmol/L (Area under curve: 0.719, specificity: 73.7%, sensitivity: 72.1%). Furthermore, plaque enhancement on HRMRI (P < 0.001), positive remodeling (P < 0.001), plaque load (P < 0.001) and luminal stenosis (P < 0.001) were superior among patients with HDL-2b < 0.21 mmol/L.Conclusions: Our data showed that serum HDL-2b levels may serve as a biomarker for predicting vulnerability in intracranial atherosclerotic plaques.

High-density lipoprotein (HDL) particles comprising heterogeneous subclasses of different functions exert anti-inflammatory effects by interacting with immune-response cells. However, the relationship of HDL subclasses with immune-response cells in metabolic unhealth/obesity has not been defined clearly. The purpose of this study was to delineate the relational changes of HDL subclasses with immune cells and inflammatory markers in metabolic unhealth/obesity to understand the role of anti-inflammatory HDL subclasses. A total of 316 participants were classified by metabolic health. HDL subclasses were detected by microfluidic chip electrophoresis. White blood cell (WBC) counts and lymphocytes were assessed using automatic haematology analyser. Levels of high-sensitivity C-reactive protein (hs-CRP) and interleukin 6 (IL-6) were measured. In our study, not only the distribution of HDL subclasses, but also HDL-related structural proteins changed with the deterioration of metabolic disease. Moreover, lymphocytes and inflammation factors significantly gradually increased. The level of HDL2b was negatively associated with WBC, lymphocytes and hs-CRP in multivariable linear regression analysis. In multinomial logistic regression analysis, high levels of HDL3 and low levels of HDL2b increased the probability of having an unfavourable metabolic unhealth/obesity status. We supposed that HDL2b particles may play anti-inflammation by negatively regulating lymphocytes activation. HDL2b may be a therapeutic target for future metabolic disease due to the anti-inflammatory effects.

Abstract [OBJECTIVES] Genetic alternations of EGFR and KRAS are frequently found in lung cancer cells. Accurate detection of these mutations from lung cancer peripheral blood may provide a noninvasive means for early cancer detection and disease monitoring. The goal of this study is to develop a quantitative analysis of EGFR and KRAS mutations both of ctDNA in plasma and of CTCs in blood cells from lung cancers by digital castPCR (competitive allele specific TaqMan-base PCR) technology. [METHODS] Molecular analysis and enumeration of CTCs in peripheral blood cells were analyzed by combining sample partition and digital castRT-qPCR assays without prior biophysical processing. The castPCR can detect rare copies of mutant alleles with a 6-log dynamic range and < 5-copy detection sensitivity for EGFR and KRAS mutations. Quantitative analysis of EGFR and KRAS mutations in ctDNA was done in OpenArray platform by digital castPCR. For CTC detection, whole blood samples with spiked-in known mutation and gen marker lung cancer cell lines were partitioned onto 96- or 384-well plate(s), such that each well contains either one cancer cell or none together with normal white blood cells and red blood cells. RNAs and/or DNAs were extracted by magnetic beads and were pre-amplified prior to molecular detection. Genetic mutations and cell type specific markers (CK19) for CTC identification and enumeration were determined by castRT-qPCR and TaqMan Gene expression (GEx) assays, respectively. Blood samples from lung cancer patients were first separated into blood cells and plasma portions before CTC detections. The sample plasma portions were used to detect EGFR and KRAS mutations of ctDNA by digital castPCR in OpenArray platform. [RESULTS] The sample partition process resulted in a relative CTC enrichment or digital enrichment of 20 - 400 folds (the relative ratio of CTC to normal cells) in a CTC-positive well. The RT-castPCR and TaqMan GEx assays accurately quantify the number of spiked-in tumor cells (10 - 60 cells/mL) in whole blood with known EGFR and/or KRAS mutations and CK19. For 10 blood samples from lung cancer patients, CTCs were detected from all patients even with stage I and II of 3 patients. In the plasma portions of the same samples, digital castPCR by OpenArray was able to detect EGFR mutations (p.L858R) and 19 mutations of EFGR exon 9. The results of EGFR mutations are consistent between intact CTCs and ctDNA. [CONCLUSION] Our preliminary data suggest that combination of digital sample enrichment and castRT-qPCR can be used to directly enumerate CTCs and detect cancer-related mutations in blood cells without prior biophysical sample enrichment. Digital castPCR by OpenArray can be used to assess circulating tumor DNA. Further test in larger clinical samples are warranted. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1736. doi:1538-7445.AM2012-1736

Abstract The discovery of pivotal genetic alterations and the understanding of their role in cancer is leading to remarkable successes in therapeutics and patient care. Molecular diagnosis methods such as DNA sequencing and conventional genotyping of tumor biopsies have advanced research in this field, but are limited in sensitivity due to stromal contamination and by genetic heterogeneity in cancer. We have recently developed competitive allele specific TaqMan® PCR (castPCR) assays assays for detecting cancer-associated sequence variations. CastPCR not only maintains the wide dynamic range, high sensitivity and reproducibility of TaqMan® assays but also greatly improves the specificity. The technology enables detection, of as little as 1 mutant allele molecule in 10,000,000 wild type molecules. We report here sensitive and accurate detection of cancer-associated KRAS mutations within formalin-fixed paraffin-embedded (FFPE) heterogeneous cancer specimens. Eight FFPE model cell lines were initially used to validate the assays (NCI-H2009:p.G12A; SW1463:p.G12C; PANC-1:p.G12D; PSN-1: p.G12R; A549:p.G12S; SW480:p.G12V; DLD-1:p.G13D; Jurkat:Wild Type). Mutant FFPE cell line DNAs were titrated in the FFPE wild type cell line DNAs from 100% to 0.1%. Mutations were easily identified at the level of 0.1% with high reproducibility. 24 anonymous tumor tissues and 12 non-tumor tissues from FFPE specimens were also examined. No positive samples were found in non-tumor tissues. The results obtained by castPCR for the 24 tumor tissues were concordant to those previously reported by three different methods (Taqman® PCR, Taqman® PCR + PNA and Sequencing). Our results demonstrate that castPCR, as a new rare mutation detection technology, has greater sensitivity, specificity and can thereby facilitate accurate molecular diagnosis of heterogeneous cancer specimens and enable patient selection for targeted cancer therapies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3071. doi:10.1158/1538-7445.AM2011-3071

ObjectiveTo accurately enumerate CFC at 1st and early 2nd trimesters and study the relationship between CFC number and gestational age for early non-invasive prenatal genetic analysisStudy DesignArtemis Health is developing a highly-efficient microfluidic process to purify fetal cells from maternal blood. As part of efforts to develop a fetal cell based early non-invasive prenatal genetic diagnostic, we developed methods to accurately enumerate CFCs in 1st and early 2nd trimesters and study the relationship between CFC numbers and gestational age. Blood samples were drawn from pre-termination pregnant women with gestational ages ranging from 6 to 19 weeks.ResultsOur fetal cell enumeration methods were able to distinguish between DNA from intact fetal cells and that from fragmented cffNA. The average number of fetal cells was 9.6 ± 7.2 cells/10 ml whole blood, and ranged from 2 – 41 cells/10 ml blood. There was no apparent correlation between the CFC number and gestational age over range of 6 to 19 weeks (see figure). In 1st trimester (6 – 13 wks), the average CFC number was 11.1 ± 8.4 cells/10 ml (n = 53), compared to 8.6. ± 6.0 (n = 17) in 2nd trimester (14 – 19 wks).ConclusionOur proprietary assay detected circulating fetal cells in all early pregnant maternal blood samples analyzed independent of gestational age, showing the potential for early non-invasive prenatal genetic diagnosis. We are further developing our microfluidic system for the efficient removal of non-target cells and the high recovery of fetal cells. ObjectiveTo accurately enumerate CFC at 1st and early 2nd trimesters and study the relationship between CFC number and gestational age for early non-invasive prenatal genetic analysis To accurately enumerate CFC at 1st and early 2nd trimesters and study the relationship between CFC number and gestational age for early non-invasive prenatal genetic analysis Study DesignArtemis Health is developing a highly-efficient microfluidic process to purify fetal cells from maternal blood. As part of efforts to develop a fetal cell based early non-invasive prenatal genetic diagnostic, we developed methods to accurately enumerate CFCs in 1st and early 2nd trimesters and study the relationship between CFC numbers and gestational age. Blood samples were drawn from pre-termination pregnant women with gestational ages ranging from 6 to 19 weeks. Artemis Health is developing a highly-efficient microfluidic process to purify fetal cells from maternal blood. As part of efforts to develop a fetal cell based early non-invasive prenatal genetic diagnostic, we developed methods to accurately enumerate CFCs in 1st and early 2nd trimesters and study the relationship between CFC numbers and gestational age. Blood samples were drawn from pre-termination pregnant women with gestational ages ranging from 6 to 19 weeks. ResultsOur fetal cell enumeration methods were able to distinguish between DNA from intact fetal cells and that from fragmented cffNA. The average number of fetal cells was 9.6 ± 7.2 cells/10 ml whole blood, and ranged from 2 – 41 cells/10 ml blood. There was no apparent correlation between the CFC number and gestational age over range of 6 to 19 weeks (see figure). In 1st trimester (6 – 13 wks), the average CFC number was 11.1 ± 8.4 cells/10 ml (n = 53), compared to 8.6. ± 6.0 (n = 17) in 2nd trimester (14 – 19 wks). Our fetal cell enumeration methods were able to distinguish between DNA from intact fetal cells and that from fragmented cffNA. The average number of fetal cells was 9.6 ± 7.2 cells/10 ml whole blood, and ranged from 2 – 41 cells/10 ml blood. There was no apparent correlation between the CFC number and gestational age over range of 6 to 19 weeks (see figure). In 1st trimester (6 – 13 wks), the average CFC number was 11.1 ± 8.4 cells/10 ml (n = 53), compared to 8.6. ± 6.0 (n = 17) in 2nd trimester (14 – 19 wks). ConclusionOur proprietary assay detected circulating fetal cells in all early pregnant maternal blood samples analyzed independent of gestational age, showing the potential for early non-invasive prenatal genetic diagnosis. We are further developing our microfluidic system for the efficient removal of non-target cells and the high recovery of fetal cells. Our proprietary assay detected circulating fetal cells in all early pregnant maternal blood samples analyzed independent of gestational age, showing the potential for early non-invasive prenatal genetic diagnosis. We are further developing our microfluidic system for the efficient removal of non-target cells and the high recovery of fetal cells.

Background: High-density lipoprotein (HDL) subfractions are among the new emerging risk factors for atherosclerosis. In particular, HDL 2b has been shown to be linked to cardiovascular risk. This study uses a novel microfluidics-based method to establish HDL 2b clinical utility using samples from the Prospective Cardiovascular Muenster (PROCAM) Study.Methods: Method performance was established by measuring accuracy, precision, linearity and inter-site precision. Serum samples from 503 individuals collected in the context of the PROCAM study were analyzed by electrophoresis on a microfluidics system. Of these, 251 were male survivors of myocardial infarction (cases), while 252 individuals were matched healthy controls. HDL cholesterol, HDL 2b concentration and HDL 2b percentage were analyzed.Results: This novel method showed satisfactory assay performance with an inter-site coefficient of variance of < 10% for HDL 2b percentage. Parallel patient testing on 52 samples between two sites resulted in a correlation coefficient of r=0.95. Significant differences were observed in the HDL 2b subfraction between cases and controls independent of other risk factors. Including HDL 2b percentage in logistic regression reduced the number of false positives from 64 to 39 and the number of false negative cases from 48 to 45, in the context of this study.Conclusions: The novel method showed satisfactory assay performance in addition to drastically reduced analysis times and improved ease of use as compared to other methods. Clinical utility of HDL 2b was demonstrated supporting the findings of previous studies.

This chapter introduces automation techniques for lipoprotein subclass separation. Discussions on fundamentals, and advantages and disadvantages of different lipoprotein subclass separation automation systems are presented along with an example of electrophoresis-assisted lab-on-a-chip automation for lipoprotein subclass separation.

Purpose: We hypothesized that DNA methylation regulates the differential expression of Y chromosome specific genes in prostate cancer. To test this hypothesis we analyzed the expression of Y chromosome specific genes in 5-aza-2 ' -deoxycytidine (5-azaC) treated and untreated prostate cancer cell lines.Materials and Methods: To test this hypothesis Y chromosome specific genes were analyzed in prostate cancer cells treated with the demethylation agent 5-azaC. Total RNA was extracted and reverse transcribed, and polymerase chain reaction was performed using gene specific primers. These primers were designed based on the sequence available in the public genome data bank. The 10 Y chromosome specific genes DAZ, CDY, SRY, RBMY1A, RBMY1H, RBMII, BPY1, BPY2, PRY and TSPY were analyzed in the PC3, ND1, DU145, LNCaP, TSUPr1 and DUPro prostate cancer cell lines by reverse transcriptase-polymerase chain reaction. Normal testis RNA was used as a positive control.Results: Of the 10 Y chromosome specific genes DAZ gene expression was lacking in all prostate cancer cell lines but after demethylation treatment with 5-azaC DAZ expression was restored. The SRY gene was also lacking in all prostate cancer cell lines except LNCaP. After demethylation SRY gene expression was restored in PC3, ND-1, DU-145, TSUPr1 and Dupro. There was no expression of the CDY and BPY2 genes before and after 5-azaC treatment in all prostate cancer cell lines. Expression of the RBMYY1A, RBMY1H and RBMII genes was lacking in all prostate cancer cell lines but after demethylation the expression of all 3 was restored in the ND1, DU-145 and LNCaP cell lines. The BPY1 gene was only expressed in LNCaP cells but after treatment with 5-azaC all other cell lines, namely PC3, ND1, DU145, LNCaP and DUPro, restored BPY gene expression. PRY gene expression was lacking in all prostate cancer cell lines but after demethylation only LNCaP restored expression of this gene. TSPY was expressed only in LNCaP but after demethylation ND-1 cells restored expression of the TSPY gene.Conclusions: To our knowledge we report the first study showing that expression of the Y chromosome specific genes DAZ, SRY, RBMY1A, RBMY1H, RBMII, BPY1, PRY and TSPY is regulated by DNA methylation in prostate cancer.